understanding wage and productivity dispersion in the united kingdom by giulia faggio, kjell g....

Understanding Wage and Productivity Dispersion in the United Kingdom

byGiulia Faggio, Kjell G. Salvanes

and John Van Reenen

Preliminary

Contents of the presentation

• Motivations• Review of the literature• Data• Description of the trends • Decomposition of wage and productivity

dispersion• Analysis of Total Factor Productivity (TFP)• Conclusions

Motivations I

• Wage inequality has increased substantially in the US and the UK over the last 30 years.

• A large proportion of this increase has been explained as a within-group phenomenon (i.e. by education, skill, occupation or industry group).

• Many theories have been proposed to explain this within-group inequality. They assume that increasing inequality takes place between firms within industries rather than within firms.

• There is almost no evidence on the impact of these between-firm effects on the aggregate increase in wage inequality and this paper tries to fill this gap.

Motivations II

• Looking at firm productivity, previous studies have analysed:– the cross-sectional distribution of firm productivity (e.g. Haltiwanger,

Lane and Spletzer, 1999)– the evolution of average productivity (e.g. Foster, Haltiwanger and

Krizan, 1998 and 2002)• Very few studies have looked at the changes of the

distribution of firm productivity over time:– Dunne, Foster, Haltiwanger and Troske (2002): they find a large

increase in wage and productivity dispersion between 1975-1992 across US manufacturing plants.

– Haskel and Martin (2002): they look at the changes in productivity dispersion focusing on UK manufacturing plants.

• This paper tries to carefully document changes in productivity dispersion over time looking at both manufacturing and non-manufacturing.

Literature• We consider three classes of theories that have tried

to explain the rising in within-group wage inequality:

1. the first group emphasizes the impact of a technological revolution that has caused differential adoption of new technology by firm (e.g. Caselli, 1999)

2. the second group links increased inequality to increased segmentation of workers by skill (e.g. Kremer and Maskin, 1996)

3. the third group argues that institutional change (e.g. union decline) has an impact on wage inequality and thus potentially on productivity dispersion

Caselli (1999)

• He models the impact of a technological revolution (e.g. the ICT revolution) on productivity and wage dispersion.

• Implications:– High skilled workers will benefit the most (if the

technology is skilled-biased), but all workers in the more productive plants will tend to receive higher wages,

– A skilled-biased technological revolution leads to an increase in the dispersion of wages and TFP across plants,

– These increases are modelled as between firm within industry effects.

Kremer and Maskin (2000)• They model the simultaneous existence of increased

wage inequality and increased segregation of workers by skill across plants.

• Implications:– If the distribution of skills across workers is dispersed &

because of the complementary between tasks, an increase in the mean skill level leads to a separating equilibrium:

• High skill/high productivity firms and low skill/low productivity firms can exist in equilibrium,

• Increased wage inequality is associated with increased labour productivity across firms (non necessarily with TFP),

• These rises are modelled as between firm with industry effects.

Union decline

• Union declines allows low wage/low productivity firms to enter the market.

• Under strong union power, these firms were non-viable because they could not satisfy union demands over wages.

• The entrance of low wage firms raises wage dispersion and thus potentially productivity dispersion.– If low wage firms employ mostly low skill workers, they

will be characterised by low productivity as well.

Our Strategy• Descriptive analysis of trends in wage dispersion and

productivity dispersion– There is limited evidence on the changes in productivity dispersion and ours is

one of the first attempts.

• Decomposition of trends in wage and productivity dispersion– Is the rising wage dispersion a within- or between-firm phenomenon?– Is the rising productivity dispersion a between-firm within-industry or

between-industry phenomenon?

• Analysis of Total Factor Productivity (TFP)– Caselli (1999)’s model implies a positive link between wage and TFP

dispersion.– Kremer and Maskin (2000)’s model suggests a positive link between wage and

labour productivity dispersion, but not necessarily TFP dispersion.

• Evaluation of the theoretical explanations of these changes• Cross-country analysis

– Since theories suggest that these are global phenomena, we want to conduct an international comparison between the UK, Norway, France and the US.

Description of the data

• We use 2 different data sets for the UK:– Financial Analysis Made Easy (FAME) data set:

• Consolidated company account data for the UK manufacturing and non-manufacturing firms

• Sample period: 1984-2002.

– New Earnings Survey (NES) data set: • Employee data taken from the UK National Insurance

Database

• It samples 1 % of the UK population

• Sample period: 1975-1999.

Description of the trends

• the UK:– Wage dispersion in private services and

manufacturing:• using data at the individual level (log real annual wage)

• using data at the firm level (log real annual average firm wage)

– Labour Productivity dispersion in private services and manufacturing:

• using data at the firm level (log real value added per worker)

Wage dispersion in the UK: private services, individual data

11

.21

.41

.61

.8

1984 1989 1994 1999year

10th percentile (indexed) 50th percentile (indexed)90th percentile (indexed)

Log hourly wage: 16-64 men

Private servicesWage Dispersion in the UK

Wage dispersion in the UK: manufacturing, individual data

11

.21

.41

.61

.8

1984 1989 1994 1999year


Log hourly wage: 16-64 men

Manufacturing industriesWage Dispersion in the UK

Wage dispersion in the UK:private services, firm level data

11

.21

.41

.61

.8

1984 1989 1994 1999year


Log average firm wage

Private servicesWage Dispersion in the UK

Wage dispersion in the UK:manufacturing, firm level data1

1.2

1.4

1.6

1.8

1984 1989 1994 1999year


Log average firm wage

Manufacturing industriesWage Dispersion in the UK

Productivity dispersion in the UK: private services, firm level data

11

.21

.41

.61

.8

1984 1989 1994 1999year


Log value added per employee

Private servicesProductivity Dispersion in the UK

Productivity dispersion in the UK: manufacturing, firm level data1

1.2

1.4

1.6

1.8

1984 1989 1994 1999year


Log value added per employee

Manufacturing industriesProductivity Dispersion in the UK

Summary of the evidence

Using individual level data:– Wage inequality was increasing in both private

services and manufacturing until the early 1990s; then it continued to increase in private services but not in manufacturing.

• Using firm level data:– Wage inequality as well as productivity dispersion

is increasing substantially in private services. Limited increase in manufacturing.

Decomposition of trends in wage and productivity dispersion

• Following Davis and Haltiwanger (1991), we decompose wage dispersion into between and within firm components:– Within firm component

– Between firm within industry component

– Between industry component

j

iji k

ijkijj i k

kij WWWWWW 22 )]()[()( (1)

Where:- Wkij is the wage for worker k at firm i in sector j, - Wij is the average wage at firm i in sector j and - W is the mean wage across all workers in all firms and sectors.

k=workeri=firmj=sector

Variance decomposition

• Multiplying and dividing the first term of the right-hand side of equation (1) by Nij (Nij = total number of workers k in firm i):

• Calling Vij the estimated variance of wages across workers of firm i, equation (2) becomes:

Total variance Within firm component Between firm component

Variance decomposition

• Dividing through by N, the total number of workers in the economy, we obtain the decomposition of overall variation into within-firm (WF) and between-firm (BF) components:

22)(

11)(

1 j i

ijijj i

ijijj i k

kij WWNN

VNN

WWN

(4)

j iijijWF VN

NV

1 , Within firm component (5)

j iijijBF WWN

NV

2)(

1 , Between firm component (6)

BFWF VVV (7)

Variance decomposition – Between component

• It is possible to decompose the between-firm variation as: – the sum of total variation of firm average wage relative to the sector

average (VBFI = between firm/within industry) – the total variation of the sector average wage relative to the average of

the whole economy (VBI = between industry):

VBF = VBFI + VBI V= VWF + VBFI + VBI

• The variance decomposition of the between component is also applied to firm productivity

Variance decomposition of yearly wages

• We combine the individual level data from the NES with the firm level data from FAME at the 2-digit industry level:– We estimate total wage variance (V) directly from the NES.

– We estimate the between components (VBFI & VBI) directly from FAME.

– The within firm component (VWF) can be estimated as a residual.

• FAME data give a measure of total annual remuneration at the firm level while NES data provide a measure of weekly gross pay. In order to make the measures comparable:1. We adjust total annual remuneration by a coefficient (0.92) taken from a

regression of log wage on log remuneration with industry, firm size and year dummies.

2. We express both measures at the annual level and in real terms (deflated by the RPI)

Variance decomposition of yearly wages0

.1.2

.3.4

.5.6

.7.8

1984 1989 1994 1999year

total variance between componentwithin firm component

NES and FAME Datasets 1984-1999.

UK manufacturing and private servicesDecomposition of wage dispersion

Variance decomposition of yearly wagesfurther decomposition of the between component

0.1

.2.3

.4.5

.6.7

.8

1984 1989 1994 1999year

total variance between firm within industry componentwithin firm component between industry component


UK manufacturing and private servicesDecomposition of Wage Dispersion

Variance decomposition of yearly wages UK private services

0.1

.2.3

.4.5

.6.7

.8

1984 1989 1994 1999year



UK private servicesDecomposition of Wage Dispersion

Variance decomposition of yearly wages UK manufacturing

0.1

.2.3

.4.5

.6.7

.8

1984 1989 1994 1999year



UK manufacturing industriesDecomposition of Wage Dispersion

Variance decomposition of labour productivity0

.1.2

.3.4

.5.6

1984 1989 1994 1999year

between firm within industry comp. between industry comp.

UK FAME Dataset 1984-1999. NES weights.

UK manufacturing and private servicesDecomposition of Labour Productivity Dispersion

Variance decomposition of labour productivity UK private services

0.1

.2.3

.4.5

.6

1984 1989 1994 1999year



UK Private ServicesDecomposition of Labour Productivity Dispersion

Variance decomposition of labour productivity UK manufacturing industries

0.1

.2.3

.4.5

.6

1984 1989 1994 1999year



UK Manufacturing IndustriesDecomposition of Labour Productivity Dispersion

Summary of the results • Evidence indicates that wage inequality and labour

productivity dispersion have increased in the UK over the period 1984-99.

• The rises in wage dispersion and in productivity dispersion are driven by increases in private services.

• We find that rising wage dispersion is largely a between-firm within-industry phenomenon rather than a within firm phenomenon.

• We find that rising labour productivity dispersion is largely a between-firm within-industry phenomenon rather than a between-industry phenomenon.

• These findings appear to give some support to explanations (e.g. Caselli, 1999, Kremer and Maskin, 2000) that link rising wage inequality to between firm effects.

Variance decomposition of TFP

ln(K)ln(L)ln(VA)TFP )(1

1. α = 0.7 as average share of labour (L) in the economy,2. α = industry specific weights (i.e. ratio of total wage bill over

value added at the 2-digit industry level),3. α = firm specific weights (i.e. ratio of total wage bill over

value added at the firm level). A preliminary analysis uses α = 0.7.

We define TFP simply as:

Variance decomposition of TFP0

.1.2

.3.4

.5.6

1984 1989 1994 1999year



UK manufacturing and private servicesDecomposition of TFP Dispersion

Variance decomposition of TFPUK private services

0.1

.2.3

.4.5

.6

1984 1989 1994 1999year



UK private servicesDecomposition of TFP Dispersion

Variance decomposition of TFPUK manufacturing industries

0.1

.2.3

.4.5

.6

1984 1989 1994 1999year



UK manufacturing industriesDecomposition of TFP Dispersion

Summary of the results - TFP

• As for wage and labour productivity dispersion, the rise in TFP dispersion is mostly driven by increases in private services.

• We find that rising TFP dispersion is largely a between-firm within-industry phenomenon rather than a between-industry phenomenon.

• However, the between-industry component seems more important in explaining TFP dispersion rather than labour productivity dispersion.

• These findings appear to give some support to Caselli (1999)’s model.

Next steps• Distinguishing between theories:

– Caselli(1999) versus Kremer and Maskin(2000)– Institutional change versus Caselli(1999)

• Measurement error issues:– We do not have information about skills, gender and part-

time/full-time workers at the firm level. Increased wage dispersion might be due to:

• Changes in the composition of workers in the firm• Higher female participation • Larger share of part-time workers

– We use remuneration instead of hourly wages– Analysis of TFP: we do not measure all inputs properly– Using employer-employee data on Norway we can deal

with some of these issues

Institutional change versus Caselli(1999):a simple framework

• UK/US: union decline and reduction in the share of workers covered by collective agreements

• France/Norway: union decline but very high share (95%in france) of workers covered by collective agreements

UK/US France/Norway

Caselli (1999)

Institutional change

σw ↑

σp ↑

σw ↑

σp ↑

σw -

σp ↑

σw -

σp -

Caselli’s channel is from productivity to wages.

Institutional channel goes from changes in wage to changes inproductivity.